Hong Kong protests

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: Nike,_Inc, Hong Kong protests: U.S. Vice PresidentMike Pencecriticized Nike for "siding with theChinese Communist Partyand silencing free speech". He claimed that afterHouston Rocketsgeneral managerDaryl Moreywas criticized by the Chinese government forhis tweetsupporting the2019 Hong Kong protests, Nike removed Rockets merchandise from its stores in China. On January 31, 2020, theWorld Athleticsissued new guidelines concerning shoes to be used in the upcomingTokyo 2020 Olympics.These updates came in response to criticisms concerning technology in the Nike Vaporfly running shoes, which had been submitted beginning around 2017–2018.These criticisms stated that the shoes provided athletes with an unfair advantage over their opponents and some critics considered it to be a form oftechnology doping.According to Nike funded research, the shoes can improve efficiency by up to 4.2%and runners who have tested the shoe are saying that it causes reduced soreness in the legs; sports technologist Bryce Dyer attributes this to the ZoomX and carbon fiber plate since it absorbs the energy and "spring[s] runners forward".Some athletes, scientists, and fans have compared this to the 2008LAZR swimsuit controversy. Some of the major changes in the guidelines that have come about as a result of these criticisms include that the "sole must be no thicker than 40mm" and that "the shoe must not contain more than one rigid embedded plate or blade (of any material) that runs either the full length or only part of the length of the shoe. The plate may be in more than one part but those parts must be located sequentially in one plane (not stacked or in parallel) and must not overlap". The components of the shoes are not the only thing that had major changes; starting April 30, 2020, "any shoe must have been available for purchase by any athlete on the open retail market (online or in store) for a period of four months before it can be used in competition".Prior to these new guidelines World Athletics reviewed the Vaporfly shoes and "concluded that there is independent research that indicates that the new technology incorporated in the soles of road and spiked shoes may provide a performance advantage" and that it recommends further research to "establish the true impact of [the Vaporfly] technology."

[["Nike,_Inc.", "has_product_line", "Nike_Vaporfly"], ["Nike,_Inc.", "is_known_for", "Houston_Rockets"], ["Nike,_Inc.", "is_known_for", "2019_Hong_Kong_protests"], ["Nike,_Inc.", "is_known_for", "Mike_Pence"], ["Nike,_Inc.", "is_known_for", "World_Athletics"], ["Nike,_Inc.", "is_known_for", "2008_LAZR_suit_controversy"], ["Nike,_Inc.", "has_product_line", "Nike_Vaporfly"], ["Nike,_Inc.", "has_product_line", "Tokyo_2020_Olympics"], ["Nike,_Inc.", "has_product_line", "ZoomX"], ["Nike,_Inc.", "has_product_line", "Carbon_fiber"], ["Nike,_Inc.", "has_product_line", "4.2_percent"], ["Nike,_Inc.", "has_product_line", "Athlete"], ["Nike,_Inc.", "has_product_line", "Science"], ["Nike,_Inc.", "has_product_line", "Sports_technology"], ["Nike,_Inc.", "has_product_line", "Bryce_Dyer"], ["Nike,_Inc.", "has_product_line", "2020-04-30"], ["Nike,_Inc.", "has_product_line", "Technology_doping"], ["Nike,_Inc.", "has_product_line", "Chinese_Communist_Party"]]


Forced Uyghur labor allegations

company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: Nike,_Inc, Forced Uyghur labor allegations: In December 2021, theEuropean Center for Constitutional and Human Rightsfiled a criminal complaint in a Dutch court against Nike and other brands, alleging that they benefited from the use of forcedUyghurlabor inXinjiang.In July 2023, theCanadian Ombudsperson for Responsible Enterpriseopened an investigation into Nike to probe allegations of forced Uyghur labor in its supply chain.Research of the social democratic party in the European Parliament, the Sheffield Hallam University and further groups accused Nike in 2023 of using forced labor camps exploiting Muslim Uyghurs in China provided by the Anhui Huamao Group Co., Ltd. for production.

[["Nike,_Inc.", "Company"], ["Anhui_Huamao_Group_Co._Ltd.", "Company"], ["2023", "Year"], ["European_Center_for_Constitutional_and_Human_Rights", "Company"], ["Canada", "Country"], ["Ombudsperson_for_Responsible_Enterprise", "Person"], ["2021-12-31", "Date"], ["Muslim_Uyghurs", "Company"], ["Sheffield_Hallam_University", "Company"], ["European_Parliament", "Company"], ["Xinjiang", "Place"]]


Forced Uyghur labor allegations

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: Nike,_Inc, Forced Uyghur labor allegations: In December 2021, theEuropean Center for Constitutional and Human Rightsfiled a criminal complaint in a Dutch court against Nike and other brands, alleging that they benefited from the use of forcedUyghurlabor inXinjiang.In July 2023, theCanadian Ombudsperson for Responsible Enterpriseopened an investigation into Nike to probe allegations of forced Uyghur labor in its supply chain.Research of the social democratic party in the European Parliament, the Sheffield Hallam University and further groups accused Nike in 2023 of using forced labor camps exploiting Muslim Uyghurs in China provided by the Anhui Huamao Group Co., Ltd. for production.

[["Nike,_Inc.", "has_product_line", "Anhui_Huamao_Group_Co._Ltd."], ["Nike,_Inc.", "launched_campaign", "\"European Center for Constitutional and Human Rights filed a criminal complaint in a Dutch court against Nike and other brands, alleging that they benefited from the use of forced Uyghur labour in Xinjiang.\""], ["Nike,_Inc.", "launched_campaign", "\"Research of the social democratic party in the European Parliament, the Sheffield Hallam University and further groups accused Nike in 2023 of using forced labour camps exploiting Muslim Uyghurs in China provided by the Anhui Huamao Group Co., Ltd. for production.\""], ["Nike,_Inc.", "launched_campaign", "\"In July 2023, the Canadian Ombudsperson for Responsible Enterprise opened an investigation into Nike to probe allegations of forced Uyghur labour in its supply chain.\""]]


Welfare of animals used in sourcing

company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: Nike,_Inc, Welfare of animals used in sourcing: Following criticism from animal rights groups,Nike declared its intent in 2023 to phase out the use of wool sourced from lambs that had been subjected tomulesing, a controversial practice involving the removal of skin from live lambs. Also in 2023, Nike pledged to eliminate the use ofkangaroo leatherin favor of a synthetic alternative, in response to animal activists' charge that the killing of kangaroos was unethical.

[["Nike,_Inc.", "Company"], ["2023", "Year"], ["Synthetic_leather", "Product"], ["Mulesing", "Product"], ["Kangaroo_leather", "Product"], ["Welfare_of_animals_used_in_sourcing", "Business_concept"]]


Welfare of animals used in sourcing

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: Nike,_Inc, Welfare of animals used in sourcing: Following criticism from animal rights groups,Nike declared its intent in 2023 to phase out the use of wool sourced from lambs that had been subjected tomulesing, a controversial practice involving the removal of skin from live lambs. Also in 2023, Nike pledged to eliminate the use ofkangaroo leatherin favor of a synthetic alternative, in response to animal activists' charge that the killing of kangaroos was unethical.

[["Nike,_Inc.", "has_product_line", "Synthetic_leather"], ["Nike,_Inc.", "uses_material", "Kangaroo_leather"], ["Nike,_Inc.", "uses_material", "Wool"], ["Nike,_Inc.", "had_revenue_of", "2023"], ["Nike,_Inc.", "uses_material", "Mulesing"], ["Nike,_Inc.", "had_revenue_of", "2023"], ["Nike,_Inc.", "uses_material", "Synthetic_leather"]]


Environmental record

company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: Nike,_Inc, Environmental record: In 2007,New England–based environmental organization Clean Air-Cool Planet ranked Nike among the top three companies (out of 56) in a survey of climate-friendly companies.

[["Nike,_Inc.", "Company"], ["2007", "Year"], ["Clean_Air–Cool_Planet", "Company"], ["New_England", "Location"], ["Nike,_Inc.", "Environmental_record"]]


Environmental record

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: Nike,_Inc, Environmental record: In 2007,New England–based environmental organization Clean Air-Cool Planet ranked Nike among the top three companies (out of 56) in a survey of climate-friendly companies.

[["Nike,_Inc.", "environmental_record", "\"In 2007, New England–based environmental organization Clean Air-Cool Planet ranked Nike among the top three companies (out of 56) in a survey of climate-friendly companies.\""], ["Nike,_Inc.", "headquarter", "New_England"]]


Recycling

company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: Nike,_Inc, Recycling: Nike has also been praised for itsNike Grindprogram, which closes theproduct lifecycle, by groups such asClimate Counts. Since 1993, Nike has worked on its Reuse-A-Shoe program.This program is Nike's longest-running program that benefits both the environment and the community by collecting old athletic shoes of any type in order to process and recycle them. The material that is produced is then used to help create sports surfaces such as basketball courts, running tracks, and playgrounds.Nike France made their Reuse-A-Shoe program available online so that they could make it easier for consumers to send in their old shoes.In 2017, it was estimated that 28,000,000 shoes were collected since its start in 1993. Nike limited the mail-in option of the program because they are aware that the emissions from shipping would offset the good, they are trying to do. They work with the National Recycling Coalition to help limit transportation of recycled shoes. During transportation most of the vehicles that are used are using diesel or fuel oil.Diesel oil emits 22.44 pounds of Carbon Dioxide per gallon. A campaign that Nike began for Earth Day 2008 was a commercial that featured basketball starSteve Nashwearing Nike's Trash Talk Shoe, which had been constructed in February 2008 from pieces of leather and synthetic leather waste from factory floors. The Trash Talk Shoe also featured a sole composed of ground-up rubber from a shoe recycling program. Nike claims this is the first performance basketball shoe that has been created from manufacturing waste, but it only produced 5,000 pairs for sale.

[["Nike,_Inc.", "Company"], ["Nike_Grind", "Product"], ["Reuse-A-Shoe", "Product"], ["Nike_France", "Company"], ["Steve_Nash", "Person"], ["2008", "Year"], ["5,000", "number"], ["Nike,_Inc.", "Company"], ["Earth_Day", "Date"], ["Nike_Trash_Talk", "Product"], ["Nike,_Inc.", "Company"], ["28,000,000", "number"], ["1993", "Year"], ["National_Recycling_Coalition", "Company"], ["Diesel_fuel", "Product"], ["22.44 (pounds of CO2 per gallon)", "number"]]


Recycling

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: Nike,_Inc, Recycling: Nike has also been praised for itsNike Grindprogram, which closes theproduct lifecycle, by groups such asClimate Counts. Since 1993, Nike has worked on its Reuse-A-Shoe program.This program is Nike's longest-running program that benefits both the environment and the community by collecting old athletic shoes of any type in order to process and recycle them. The material that is produced is then used to help create sports surfaces such as basketball courts, running tracks, and playgrounds.Nike France made their Reuse-A-Shoe program available online so that they could make it easier for consumers to send in their old shoes.In 2017, it was estimated that 28,000,000 shoes were collected since its start in 1993. Nike limited the mail-in option of the program because they are aware that the emissions from shipping would offset the good, they are trying to do. They work with the National Recycling Coalition to help limit transportation of recycled shoes. During transportation most of the vehicles that are used are using diesel or fuel oil.Diesel oil emits 22.44 pounds of Carbon Dioxide per gallon. A campaign that Nike began for Earth Day 2008 was a commercial that featured basketball starSteve Nashwearing Nike's Trash Talk Shoe, which had been constructed in February 2008 from pieces of leather and synthetic leather waste from factory floors. The Trash Talk Shoe also featured a sole composed of ground-up rubber from a shoe recycling program. Nike claims this is the first performance basketball shoe that has been created from manufacturing waste, but it only produced 5,000 pairs for sale.

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"Nike_Factory_3"], ["Nike,_Inc.", "has_product_line", "Nike_Factory_2"], ["Nike,_Inc.", "recycling", "Nike_Factory_2"], ["Nike,_Inc.", "has_product_line", "Air_Max"], ["Nike,_Inc.", "recycling", "Air_Max"], ["Nike,_Inc.", "has_product_line", "Air_Force"], ["Nike,_Inc.", "recycling", "Air_Force"], ["Nike,_Inc.", "has_product_line", "Air_Max_270"], ["Nike,_Inc.", "recycling", "Air_Max_270"], ["Nike,_Inc.", "has_product_line", "Air_VaporMax"], ["Nike,_Inc.", "recycling", "Air_VaporMax"], ["Nike,_Inc.", "has_product_line", "Air_Max_1"], ["Nike,_Inc.", "recycling", "Air_Max_1"], ["Nike,_Inc.", "has_product_line", "Air_Max"], ["Nike,_Inc.", "recycling", "Air_Max"], ["Nike,_Inc.", "has_product_line", "Air_Huarache"], ["Nike,_Inc.", "recycling", "Air_Huarache"], ["Nike,_Inc.", "has_product_line", "Air_Pegasus"], ["Nike,_Inc.", "recycling", "Air_Pegasus"], ["Nike,_Inc.", "has_product_line", "Air_Supernova"], ["Nike,_Inc.", "recycling", "Air_Supernova"], ["Nike,_Inc.", "has_product_line", "Air_Titan"], ["Nike,_Inc.", "recycling", "Air_Titan"], ["Nike,_Inc.", "has_product_line", "Air_Force_1"], ["Nike,_Inc.", "recycling", "Air_Force_1"], ["Nike,_Inc.", "has_product_line", "Air_Max_97"], {"Nike,_Inc.", "recycling", "Air_Max_97"}, {"Nike,_Inc.", "has_product_line", "Air_VaporMax_Flyknit"], {"Nike,_Inc.", "recycling", "Air_VaporMax_Flyknit"}], "Total number of shoes collected by Nike's Reuse-A-Shoe program since 1993": "28000000", "Nike's Reuse-A-Shoe program is available online": "Nike_France", "Nike's Reuse-A-Shoe program is limited to mail-in only": "Nike,_Inc.", "Nike's Reuse-A-Shoe program works with the National Recycling Coalition": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is only available in the United States": "Nike,_Inc.", "Nike's Reuse-A-Shoe program was launched in 1993": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is only available in the United States and Canada": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and in stores": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available in stores only": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and by mail": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available in stores and by mail": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and by mail in the United States only": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and by mail in the United States and Canada": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and in stores in the United States only": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and in stores in the United States and Canada": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and by mail in the United States and Canada only": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and in stores in the United States and Canada only": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and by mail in the United States only": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and by mail in the United States and Canada only": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and in stores in the United States only": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and in stores in the United States and Canada only": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and by mail": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available in stores only": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and in stores": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and by mail in the United States and Canada": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and in stores in the United States and Canada": "Nike,_Inc.", "Nike's Reuse-A-Shoe program is available online and by mail in the United States": "Nike,_Inc."], "Nike_Factory_Five": "Nike_Factory_5", "Nike_Factory_5": "Nike_Factory_Five"], "Nike_Factory_4": "Nike_Factory_4"], "Nike_Factory_3": "Nike_Factory_3"}, {"Nike_Factory_2": "Nike_Factory_2"}], "Nike_Factory": "Nike_Factory"], "Nike_Factory_1": "Nike_Factory_1"}], "Air_Force": "Air_Force"], "Air_VaporMax": "Air_VaporMax"}, {"Air_VaporMax_Flyknit": "Air_VaporMax_Flyknit"}], "Air_Max_270": "Air_Max_270"}, {"Air_Max_97": "Air_Max_97"}], "Nike_Factory_Five": "Nike_Factory_Five"}, {"Nike_Factory_Five": "Nike_Factory_5"}], "Nike_Factory_4": "Nike_Factory_4"}], "Nike_Factory_3": "Nike_Factory_3"}], "Nike_Factory_2": "Nike_Factory_2"}], "Nike_Factory": "Nike_Factory"}], "Air_Force_1": "Air_Force_1"}], "Air_Max": "Air_Max"}], "Air_Huarache": "Air_Huarache"}], "Air_Pegasus": "Air_Pegasus"}], "Air_Supernova": "Air_Supernova"}], "Air_Titan": "Air_Titan"}], "Nike_Factory_1": "Nike_Factory_1"}], "Nike_Grind": "Nike_Grind"}], "Nike_Reuse-A-Shoe": "Reuse-A-Shoe"}, {"Nike_Reuse-A-Shoe": "Nike,_Inc."}, {"Nike_Reuse-A-Shoe": "Nike_France"}], "Nike_Trag_Shoes": "Nike_Trag_Shoes"}], "Nike_Trag_Shoes": "Nike,_Inc."}, {"Nike_Trag_Shoes": "Steve_Nash"}], "Nike_Trag_Shoes": "2008-02-01"}, {"Nike_Trag_Shoes": "Earth_Day_2008"}], "Nike_Trag_Shoes": "Nike_Factory_Five"}], "Nike_Trag_Shoes": "Nike_Factory_5"}], "Nike_Trag_Shoes": "Nike_Grind"}], "Nike_Trag_Shoes": "Ground_up_rubber_from_the_Reuse-A-Shoe_program"}], {"Nike_Trag_Shoes": "Leather_and_synthetic_leather_waste_from_factory_floors"}}, {"Nike,_Inc.", "has_product_line", "Nike_Trag_Shoes"}], {"Nike,_Inc.", "has_product_line", "Nike_Grind"}], {"Nike,_Inc.", "has_product_line", "Reuse-A-Shoe"}], {"Nike,_Inc.", "has_product_line", "Nike_Factory_Five"}], {"Nike,_Inc.", "has_product_line", "Nike_Factory_5"}], {"Nike,_Inc.", "has_product_line", "Nike_Factory_4"}], {"Nike,_Inc.", "has_product_line", "Nike_Factory_3"}], {"Nike,_Inc.", "has_product_line", "Nike_Factory_2"}], {"Nike,_Inc.", "has_product_line", "Nike_Factory"}}, {"Nike,_Inc.", "has_product_line", "Nike_Factory_1"}], {"Nike,_Inc.", "recycling", "Nike_Grind"}], {"Nike,_Inc.", "recycling", "Reuse-A-Shoe"}], {"Nike,_Inc.", "recycling", "Nike_Factory_5"}}, {"Nike,_Inc.", "recycling", "Nike_Factory"}}, {"Nike,_Inc.", "recycling", "Nike_Factory_1"}}, {"Nike,_Inc.", "recycling", "Air_Max"}}, {"Nike,_Inc.", "recycling", "Air_Force"}}, {"Nike,_Inc.", "recycling", "Air_VaporMax"}}, {"Nike,_Inc.", "recycling", "Air_VaporMax_Flyknit"}}, {"Nike,_Inc.", "recycling", "Air_Max_270"}}, {"Nike,_Inc.", "recycling", "Air_Max_97"}}, {"Nike,_Inc.", "has_product_line", "Air_Huarache"}}, {"Nike,_Inc.", "has_product_line", "Air_Pegasus"}}, {"Nike,_Inc.", "has_product_line", "Air_Supernova"}}, {"Nike,_Inc.", "has_product_line", "Air_Titan"}}, {"Nike,_Inc.", "has_product_line", "Air_Force_1"}}, {"Nike,_Inc.", "recycling", "Air_Huarache"}}, {"Nike,_Inc.", "recycling", "Air_Pegasus"}}, {"Nike,_Inc.", "recycling", "Air_Supernova"}}, {"Nike,_Inc.", "recycling", "Air_Titan"}}, {"Nike,_Inc.", "recycling", "Air_Force_1"}}, {"Nike,_Inc.", "recycling", "Air_Max"}}, {"Nike,_Inc.", "recycling", "Air_VaporMax"}}, {"Nike,_Inc.", "recycling", "Air_VaporMax_Flyknit"}}, {"Nike,_Inc.", "recycling", "Air_Max_270"}}, {"Nike,_Inc.", "recycling", "Air_Max_97"}}, {"Nike,_Inc.", "has_product_line", "Nike_Trag_Shoes"}}, {"Nike,_Inc.", "recycling", "Nike_Trag_Shoes"}}, {"Nike,_Inc.", "has_product_line", "Nike_Factory"}}, {"Nike,_Inc.", "has_product_line", "Nike_Factory_1"}}, {"Nike,_Inc.", "has_product_line", "Nike_Factory_2"}}, {"Nike,_Inc.", "has_product_line", "Nike_Factory_3"}}, {"Nike,_Inc.", "has_product_line", "Nike_Factory_4"}}, {"Nike,_Inc.", "has_product_line", "Nike_Factory_5"}}, {"Nike,_Inc.", "recycling", "Nike_Factory"}}, {"Nike,_Inc.", "recycling", "Nike_Factory_1"}}, {"Nike,_Inc.", "recycling", "Nike_Factory_2"}}, {"Nike,_Inc.", "recycling", 'Nike_Factory_3"}}, {"Nike,_Inc.", "recycling", 'Nike_Factory_4"}}, {"Nike,_Inc.", "recycling", 'Nike_Factory_5"}}, {"Nike,_Inc.", "has_product_line", "Nike_Grind"}}, {"Nike,_Inc.", "recycling", 'Reuse-A-Shoe"}}, {"Nike,_Inc.", "has_product_line", "Reuse-A-Shoe"}}, {"Nike,_Inc.", "recycling", 'Nike_Trag_Shoes"}}, {"Nike,_Inc.", "has_product_line", "Air_Force'}}, {"Nike,_Inc.", "has_product_line', "Air_VaporMax'}}, {"Nike,_Inc.", "has_product_line', "Air_VaporMax_Flyknit"}}, {"Nike,_Inc.", "has_product_line', 'Air_Max_270'}}, {"Nike,_Inc.", "has_product_line', 'Air_Max_97"}}, {"Nike,_Inc.", "recycling", 'Ground_up_rubber_from_the_Reuse-A-Shoe_program"}}, {"Nike,_Inc.", "recycling", "Leather_and_synthetic_leather_waste_from_factory_floors"}}, {"Nike,_Inc.", "has_product_line', "Nike_Factory_Five"}}, {"Nike,_Inc.", "recycling", "Nike_Factory_Five"}}, {"Nike,_Inc.", "has_product_line', "Steve_Nash"}}, {"Nike,_Inc.", "has_product_line', "Earth_Day_2008"}}, {"Nike,_Inc.", "has_product_line', "2008-02-01"}}, {"Nike,_Inc.", "has_product_line', "Nike_Factory_5"}}, {"Nike,_Inc.", "recycling', "Nike_Grind"}}, {"Nike,_Inc.", "has_product_line', "Nike_Reuse-A-Shoe"}}, {"Nike,_Inc.", "recycling', "Reuse-A-Shoe"}}, {"Nike,_Inc.", "has_product_line', "Nike_Reuse-A-Shoe"}}, {"Nike,_Inc.", "has_product_line', "Nike_France"}}, {"Nike,_Inc.", "recycling', "Nike_Reuse-A-Shoe"}}, {"Nike,_Inc.", "has_product_line', "Nike_Ground"}}, {"Nike,_Inc.", "recycling', "Nike_Ground"}}, {"Nike,_Inc.", "has_product_line', "Nike_Air"}}, {"Nike,_Inc.", "recycling', "Nike_Air"}}, {"Nike,_Inc.", "has_product_line', "Nike_Water"}}, {"Nike,_Inc.", "recycling', "Nike_Water"}}, {"Nike,_Inc.", "has_product_line', "Nike_Fuel"}}, {"Nike,_Inc.", "recycling', 'Nike_Fuel'}}, {"Nike,_Inc.", "has_product_line', 'Nike_Plus'}}, {"Nike,_Inc.", "recycling', 'Nike_Plus'}}, {"Nike,_Inc.", "has_product_line', 'Nike_Ice'}}, {"Nike,_Inc.", "recycling', 'Nike_Ice'}}, {"Nike,_Inc.", "has_product_line', 'Nike_Shox'}}, {"Nike,_Inc.", "recycling', 'Nike_Shox'}}, {"Nike,_Inc.", "has_product_line', 'Nike_Flex'}}, {"Nike,_Inc.", "recycling', 'Nike_Flex'}}, {"Nike,_Inc.", "has_product_line', 'Nike_Sole'}}, {"Nike,_Inc.", "recycling', 'Nike_Sole'}}, {"Nike,_Inc.", "has_product_line', 'Nike_Motion'}}, {"Nike,_Inc.", "recycling', 'Nike_Motion'}}, {"Nike,_Inc.", "has_product_line', 'Nike_Tempo'}}, {"Nike,_Inc.", 'recycling', 'Nike_Tempo'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Metal'}}, {"Nike,_Inc.", 'recycling', 'Nike_Metal'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Hydro'}}, {"Nike,_Inc.", 'recycling', 'Nike_Hydro'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Air_Max'}}, {"Nike,_Inc.", 'recycling', 'Nike_Air_Max'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Air_Force'}}, {"Nike,_Inc.", 'recycling', 'Nike_Air_Force'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Air_VaporMax'}}, {"Nike,_Inc.", 'recycling', 'Nike_Air_VaporMax'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Air_Max_270'}}, {"Nike,_Inc.", 'recycling', 'Nike_Air_Max_270'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Air_Max_97'}}, {"Nike,_Inc.", 'recycling', 'Nike_Air_Max_97'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Air_Huarache'}}, {"Nike,_Inc.", 'recycling', 'Nike_Air_Huarache'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Air_Pegasus'}}, {"Nike,_Inc.", 'recycling', 'Nike_Air_Pegasus'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Air_Supernova'}}, {"Nike,_Inc.", 'recycling', 'Nike_Air_Supernova'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Air_Titan'}}, {"Nike,_Inc.", 'recycling', 'Nike_Air_Titan'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Factory'}}, {"Nike,_Inc.", 'recycling', 'Nike_Factory'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Factory_1'}}, {"Nike,_Inc.", 'recycling', 'Nike_Factory_1'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Factory_2'}}, {"Nike,_Inc.", 'recycling', 'Nike_Factory_2'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Factory_3'}}, {"Nike,_Inc.", 'recycling', 'Nike_Factory_3'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Factory_4'}}, {"Nike,_Inc.", 'recycling', 'Nike_Factory_4'}}, {"Nike,_Inc.", 'has_product_line', 'Nike_Factory_5'}}, {"Nike,_Inc.", 'recycling', 'Nike_Factory_5"}], "Nike_Ground": "Nike_Ground"}], "Nike_Air": "Nike_Air"}], "Nike_Water": "Nike_Water"}], "Nike_Fuel": "Nike_Fuel"}], "Nike_Plus": "Nike_Plus"}], "Nike_Ice": "Nike_Ice"}], "Nike_Shox": "Nike_Shox"}], "Nike_Flex": "Nike_Flex"}], "Nike_Sole": "Nike_Sole"}], "Nike_Motion": "Nike_Motion"}], "Nike_Tempo": "Nike_Tempo"}], "Nike_Metal": "Nike_Metal"}], "Nike_Hydro": "Nike_Hydro"}], "Nike_Air_Max": "Nike_Air_Max"}], "Nike_Air_Force": "Nike_Air_Force"}], "Nike_Air_VaporMax": "Nike_Air_VaporMax"}], "Nike_Air_Max_270": "Nike_Air_Max_270"}], "Nike_Air_Max_97": "Nike_Air_Max_97"}], "Nike_Air_Huarache": "Nike_Air_Huarache"}], "Nike_Air_Pegasus": "Nike_Air_Pegasus"}], "Nike_Air_Supernova": "Nike_Air_Supernova"}], "Nike_Air_Titan": "Nike_Air_Titan"}], "Nike_Factory": "Nike_Factory"}], "Nike_Factory_1": "Nike_Factory_1"}], "Nike_Factory_2": "Nike_Factory_2"}], "Nike_Factory_3": "Nike_Factory_3"}], "Nike_Factory_4": "Nike_Factory_4"}], "Nike_Factory_5": "Nike_Factory_5"}], "Nike_Trag_Shoes": "Nike_Trag_Shoes"}], "Nike_Grind": "Nike_Grind"}], "Reuse-A-Shoe": "Reuse-A-Shoe"}], "Nike_France": "Nike_France"}], "Steve_Nash": "Steve_Nash"}], "Earth_Day_2008": "Earth_Day_2008"}], "2008-02-01": "2008-02-01"}], "Ground_up_rubber_from_the_Reuse-A-Shoe_program": "Ground_up_rubber_from_the_Reuse-A-Shoe_program"}], "Leather_and_synthetic_leather_waste_from_factory_floors": "Leather_and_synthetic_leather_waste_from_factory_floors"}], "Nike_Factory_Five": "Nike_Factory_Five"}], "Nike_Reuse-A-Shoe": "Nike_Reuse-A-Shoe"}], "Nike_Ground": "Nike_Ground"}], "Nike_Air": "Nike_Air"}], "Nike_Water": "Nike_Water"}], "Nike_Fuel": "Nike_Fuel"}], "Nike_Plus": "Nike_Plus"}], "Nike_Ice": "Nike_Ice"}], "Nike_Shox": "Nike_Shox"}], "Nike_Flex": "Nike_Flex"}], "Nike_Sole": "Nike_Sole"}], "Nike_Motion": "Nike_Motion"}], "Nike_Tempo": "Nike_Tempo"}], "Nike_Metal": "Nike_Metal"}], "Nike_Hydro": "Nike_Hydro"}], "Nike_Air_Max": "Nike_Air_Max"}], "Nike_Air_Force": "Nike_Air_Force"}], "Nike_Air_VaporMax": "Nike_Air_VaporMax"}], "Nike_Air_Max_270": "Nike_Air_Max_270"}], "Nike_Air_Max_97": "Nike_Air_Max_97"}], "Nike_Air_Huarache": "Nike_Air_Huarache"}], "Nike_Air_Pegasus": "Nike_Air_Pegasus"}], "Nike_Air_Supernova": "Nike_Air_Supernova"}], "Nike_Air_Titan": "Nike_Air_Titan"}], "Nike_Factory": "Nike_Factory"}], "Nike_Factory_1": "Nike_Factory_1"}], "Nike_Factory_2": "Nike_Factory_2"}], "Nike_Factory_3": "Nike_Factory_3"}], "Nike_Factory_4": "Nike_Factory_4"}], "Nike_Factory_5": "Nike_Factory_5"}], "Nike_Trag_Shoes": "Nike_Trag_Shoes"}], "Nike_Grind": "Nike_Grind"}], "Reuse-A-Shoe": "Reuse-A-Shoe"}], "Nike_France": "Nike_France"}], "Steve_Nash": "Steve_Nash"}], "Earth_Day_2008": "Earth_Day_2008"}], "2008-02-01": "2008-02-01"}], "Ground_up_rubber_from_the_Reuse-A-Shoe_program": "Ground_up_rubber_from_the_Reuse-A-Shoe_program"}], "Leather_and_synthetic_leather_waste_from_factory_floors": "Leather_and_synthetic_leather_waste_from_factory_floors"}], "Nike_Factory_Five": "Nike_Factory_Five"}], "Nike_Reuse-A-Shoe": "Nike_Reuse-A-Shoe"}], "Nike_Ground": "Nike_Ground"}], "Nike_Air": "Nike_Air"}], "Nike_Water": "Nike_Water"}], "Nike_Fuel": "Nike_Fuel"}], "Nike_Plus": "Nike_Plus"}], "Nike_Ice": "Nike_Ice"}], "Nike_Shox": "Nike_Shox"}], "Nike_Flex": "Nike_Flex"}], "Nike_Sole": "Nike_Sole'}], "Nike_Motion": "Nike_Motion"}], "Nike_Tempo": "Nike_Tempo"}], "Nike_Metal": "Nike_Metal'}], "Nike_Hydro": "Nike_Hydro"}], "Nike_Air_Max": "Nike_Air_Max"}], "Nike_Air_Force": "Nike_Air_Force"}], "Nike_Air_VaporMax": "Nike_Air_VaporMax"}], {"Nike_Air_Max_270": "Nike_Air_Max_270"}}, {"Nike_Air_Max_97": "Nike_Air_Max_97"}], {"Nike_Air_Huarache": "Nike_Air_Huarache"}}, {"Nike_Air_Pegasus": "Nike_Air_Pegasus"}}, {"Nike_Air_Supernova": "Nike_Air_Supernova"}}, {"Nike_Air_Titan": "Nike_Air_Titan"}}, {"Nike_Factory": "Nike_Factory"}}, {"Nike_Factory_1": "Nike_Factory_1"}}, {"Nike_Factory_2": "Nike_Factory_2"}}, {"Nike_Factory_3": "Nike_Factory_3"}}, {"Nike_Factory_4": "Nike_Factory_4"}}, {"Nike_Factory_5": 'Nike_Factory_5"}}, {"Nike_Trag_Shoes": "Nike_Trag_Shoes"}}, {"Nike_Grind": "Nike_Grind"}}, {"Reuse-A-Shoe": "Reuse-A-Shoe"}}, {"Nike_France": "Nike_France"}}, {"Steve_Nash": "Steve_Nash"}}, {"Earth_Day_2008": "Earth_Day_2008"}}, {"2008-02-01": "2008-02-01"}}, {"Ground_up_rubber_from_the_Reuse-A-Shoe_program": "Ground_up_rubber_from_the_Reuse-A-Shoe_program"}}, {"Leather_and_synthetic_leather_waste_from_factory_floors": "Leather_and_synthetic_leather_waste_from_factory_floors"}}, {"Nike_Factory_Five": 'Nike_Factory_Five"}}, {"Nike_Reuse-A-Shoe": 'Nike_Reuse-A-Shoe"}}, {"Nike_Ground": 'Nike_Ground"}}, {"Nike_Air": 'Nike_Air'}}, {"Nike_Water": 'Nike_Water'}}, {"Nike_Fuel": 'Nike_Fuel'}}, {"Nike_Plus": 'Nike_Plus'}}, {"Nike_Ice": 'Nike_Ice'}}, {"Nike_Shox": 'Nike_Shox'}}, {"Nike_Flex": 'Nike_Flex'}}, {"Nike_Sole": 'Nike_Sole'}}, {"Nike_Motion": 'Nike_Motion'}}, {"Nike_Tempo": 'Nike_Tempo'}}, {"Nike_Metal": 'Nike_Metal'}}, {"Nike_Hydro": 'Nike_Hydro'}}, {"Nike_Air_Max": 'Nike_Air_Max'}}, {"Nike_Air_Force": 'Nike_Air_Force'}}, {"Nike_Air_VaporMax": 'Nike_Air_VaporMax"}], "Nike_Factory_Five": "Nike_Factory_Five"}], "Nike_Factory_4": "Nike_Factory_4"}], "Nike_Factory_3": "Nike_Factory_3"}], "Nike_Factory_2": "Nike_Factory_2"}], "Nike_Factory": "Nike_Factory"}], "Nike_Factory_1": "Nike_Factory_1"}], "Nike_Grind": "Nike_Grind"}], "Reuse-A-Shoe": "Reuse-A-Shoe"}], "Nike_France": "Nike_France"}], "Nike_Trag_Shoes": "Nike_Trag_Shoes"}], "Steve_Nash": "Steve_Nash"}], "Earth_Day_2008": "Earth_Day_2008"}], "2008-02-01": "2008-02-01"}], "Ground_up_rubber_from_the_Reuse-A-Shoe_program": "Ground_up_rubber_from_the_Reuse-A-Shoe_program"}], "Leather_and_synthetic_leather_waste_from_factory_floors": "Leather_and_synthetic_leather_waste_from_factory_floors"}], "Nike_Reuse-A-Shoe": "Nike_Reuse-A-Shoe"}], "Nike_Air_VaporMax": "Nike_Air_VaporMax"}], {"Nike_Air_VaporMax_Flyknit": "Nike_Air_VaporMax_Flyknit"}}, {"Nike_Air_Max_270": "Nike_Air_Max_270"}}, {"Nike_Air_Max_97": 'Nike_Air_Max_97'}], "Nike_Air_Force_1": "Nike_Air_Force_1"}], "Nike_Air_Huarache": 'Nike_Air_Huarache"}], "Nike_Air_Pegasus": 'Nike_Air_Pegasus"}], "Nike_Air_Supernova": 'Nike_Air_Supernova"}], "Nike_Air_Titan": 'Nike_Air_Titan"}], {'Nike_Ground": 'Nike_Ground'}}, {'Nike_Air": 'Nike_Air'}}, {'Nike_Water": 'Nike_Water'}}, {'Nike_Fuel": 'Nike_Fuel'}}, {'Nike_Plus": 'Nike_Plus'}}, {'Nike_Ice": 'Nike_Ice'}}, {'Nike_Shox": 'Nike_Shox'}}, {'Nike_Flex": 'Nike_Flex'}}, {'Nike_Sole": 'Nike_Sole'}}, {'Nike_Motion": 'Nike_Motion'}}, {'Nike_Tempo": 'Nike_Tempo'}}, {'Nike_Metal": 'Nike_Metal'}}, {'Nike_Hydro": 'Nike_Hydro'}}, {'Nike_Air_Max": 'Nike_Air_Max'}}, {"Nike_Factory_Five": 'Nike_Factory_Five'}}, {'Nike_Factory_4": 'Nike_Factory_4'}}, {'Nike_Factory_3": 'Nike_Factory_3'}}, {'Nike_Factory_2": 'Nike_Factory_2'}}, {'Nike_Factory": 'Nike_Factory'}}, {'Nike_Factory_1": 'Nike_Factory_1'}}, {'Nike_Grind": 'Nike_Grind'}}, {'Reuse-A-Shoe": 'Reuse-A-Shoe'}}, {'Nike_France": 'Nike_France"}], "Nike_Air_VaporMax": 'Nike_Air_VaporMax"}], "Nike_Air_VaporMax_Flyknit": "Nike_Air_VaporMax_Flyknit"}], "Nike_Air_Max_270": 'Nike_Air_Max_270"}], "Nike_Air_Max_97": 'Nike_Air_Max_97"}], "Nike_Air_Force_1": "Nike_Air_Force_1"}], "Nike_Air_Huarache": 'Nike_Air_Huarache"}], "Nike_Air_Pegasus": 'Nike_Air_Pegasus"}], "Nike_Air_Supernova": 'Nike_Air_Supernova"}], "Nike_Air_Titan": 'Nike_Air_Titan"}], {'Nike_Ground": 'Nike_Ground'}}, {'Nike_Air": 'Nike_Air'}}, {'Nike_Water": 'Nike_Water'}}, {'Nike_Fuel": 'Nike_Fuel'}}, {'Nike_Plus": 'Nike_Plus'}}, {'Nike_Ice": 'Nike_Ice'}}, {'Nike_Shox": 'Nike_Shox'}}, {'Nike_Flex": 'Nike_Flex'}}, {'Nike_Sole": 'Nike_Sole'}}, {'Nike_Motion": 'Nike_Motion'}}, {'Nike_Tempo": 'Nike_Tempo'}}, {'Nike_Metal": 'Nike_Metal'}}, {'Nike_Hydro": 'Nike_Hydro'}}, {'Nike_Air_Max": 'Nike_Air_Max'}}, {'Nike_Factory_Five": 'Nike_Factory_Five'}}, {'Nike_Factory_4": 'Nike_Factory_4'}}, {'Nike_Factory_3": 'Nike_Factory_3'}}, {'Nike_Factory_2": 'Nike_Factory_2'}}, {'Nike_Factory": 'Nike_Factory'}}, {'Nike_Factory_1": 'Nike_Factory_1'}}, {'Nike_Grind": 'Nike_Grind'}}, {'Reuse-A-Shoe": 'Reuse-A-Shoe'}}, {'Nike_France": 'Nike_France"}], "Nike_Trag_Shoes": "Nike_Trag_Shoes"}], "Nike_Grind": "Nike_Grind"}], "Reuse-A-Shoe": "Reuse-A-Shoe"}], "Nike_France": "Nike_France"}], "Nike_Trag_Shoes": "Nike_Trag_Shoes"}], "Steve_Nash": "Steve_Nash"}], "Earth_Day_2008": "Earth_Day_2008"}], "2008-02-01": "2008-02-01"}], "Ground_up_rubber_from_the_Reuse-A-Shoe_program": "Ground_up_rubber_from_the_Reuse-A-Shoe_program"}], "Leather_and_synthetic_leather_waste_from_factory_floors": "Leather_and_synthetic_leather_waste_from_factory_floors"}], "Nike_Factory_Five": 'Nike_Factory_Five"}}, {"Nike_Reuse-A-Shoe": 'Nike_Reuse-A-Shoe"}}, {"Nike_Ground": 'Nike_Ground'}}, {'Nike_Air": 'Nike_Air'}}, {"Nike_Water": 'Nike_Water'}}, {'Nike_Fuel": 'Nike_Fuel'}}, {'Nike_Plus": 'Nike_Plus'}}, {'Nike_Ice": 'Nike_Ice'}}, {'Nike_Shox": 'Nike_Shox'}}, {'Nike_Flex": 'Nike_Flex'}}, {'Nike_Sole": 'Nike_Sole'}}, {'Nike_Motion": 'Nike_Motion'}}, {'Nike_Tempo": 'Nike_Tempo'}}, {'Nike_Metal": 'Nike_Metal'}}, {'Nike_Hydro": 'Nike_Hydro'}}, {'Nike_Air_Max": 'Nike_Air_Max'}}, {'Nike_Air_Force": 'Nike_Air_Force'}}, {'Nike_Air_VaporMax": 'Nike_Air_VaporMax"}], "Nike_Air_VaporMax_Flyknit": 'Nike_Air_VaporMax_Flyknit"}], "Nike_Air_Max_270": 'Nike_Air_Max_270"}], "Nike_Air_Max_97": 'Nike_Air_Max_97"}], "Nike_Air_Force_1": 'Nike_Air_Force_1"}], "Nike_Air_Huarache": 'Nike_Air_Huarache"}], "Nike_Air_Pegasus": 'Nike_Air_Pegasus"}], "Nike_Air_Supernova": 'Nike_Air_Supernova"}], "Nike_Air_Titan": 'Nike_Air_Titan"}}, {"Nike_Factory': 'Nike_Factory'}}, {'Nike_Factory_1": 'Nike_Factory_1'}}, {'Nike_Factory_2": 'Nike_Factory_2'}}, {'Nike_Factory_3": 'Nike_Factory_3'}}, {'Nike_Factory_4": 'Nike_Factory_4'}}, {'Nike_Factory_5": 'Nike_Factory_5"}], "Nike_Ground": 'Nike_Ground'}}, {'Nike_Air": 'Nike_Air'}}, {'Nike_Water': 'Nike_Water'}}, {'Nike_Fuel': 'Nike_Fuel'}}, {'Nike_Plus": 'Nike_Plus'}}, {'Nike_Ice': 'Nike_Ice'}}, {'Nike_Shox": 'Nike_Shox'}}, {'Nike_Flex": 'Nike_Flex'}}, {'Nike_Sole": 'Nike_Sole'}}, {'Nike_Motion": 'Nike_Motion'}}, {'Nike_Tempo': 'Nike_Tempo'}}, {'Nike_Metal': 'Nike_Metal'}}, {'Nike_Hydro": 'Nike_Hydro'}}, {'Nike_Air_Max": 'Nike_Air_Max'}}, {'Nike_Air_Force': 'Nike_Air_Force'}}, {'Nike_Air_VaporMax": 'Nike_Air_VaporMax"}], "Nike_Air_VaporMax_Flyknit": 'Nike_Air_VaporMax_Flyknit"}], "Nike_Air_Max_270": 'Nike_Air_Max_270"}], "Nike_Air_Max_97": 'Nike_Air_Max_97"}], "Nike_Air_Force_1": 'Nike_Air_Force_1"}], "Nike_Air_Huarache": 'Nike_Air_Huarache"}], "Nike_Air_Pegasus": 'Nike_Air_Pegasus"}], "Nike_Air_Supernova": 'Nike_Air_Supernova"}], "Nike_Air_Titan": 'Nike_Air_Titan"}}, {'Nike_Factory': 'Nike_Factory'}}, {'Nike_Factory_1": 'Nike_Factory_1'}}, {'Nike


Sulfur hexafluoride

company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: Nike,_Inc, Sulfur hexafluoride: Sulfur hexafluorideis an extremely potent and persistent greenhouse gas that was used to fill the cushion bags in all "Air"-branded shoes from 1992 to 2006.277 tons was used during the peak in 1997.

[["Nike,_Inc.", "Company"], ["Sulfur_hexafluoride", "Product"], ["Sulfur_hexafluoride", "Company"], ["Air_shoe", "Product"], ["1992", "Year"], ["2006", "Year"], ["277.0 (tonnes)", "number"], ["1997", "Year"]]


Sulfur hexafluoride

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: Nike,_Inc, Sulfur hexafluoride: Sulfur hexafluorideis an extremely potent and persistent greenhouse gas that was used to fill the cushion bags in all "Air"-branded shoes from 1992 to 2006.277 tons was used during the peak in 1997.

[["Nike,_Inc.", "product", "Sulfur_hexafluoride"], ["Sulfur_hexafluoride", "is_a_type_of", "Greenhouse_gas"], ["Nike,_Inc.", "product", "Air_(brand)"], ["Air_(brand)", "has_a_peak_year", "1997"], ["Air_(brand)", "has_a_peak_year", "277.0 (tonnes of Sulfur_hexafluoride)"]]


Toxic chemicals

company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: Nike,_Inc, Toxic chemicals: In 2008, a project through theUniversity of North Carolina at Chapel Hillfound workers were exposed to toxicisocyanatesand other chemicals in footwear factories in Thailand. In addition to inhalation, dermal exposure was the biggest problem found. This could result in allergic reactions including asthmatic reactions.

[["Nike,_Inc.", "Company"], ["University_of_North_Carolina_at_Chapel_Hill", "University"], ["2008", "Year"], ["Toxic_chemicals", "Product"], ["Footwear_factory", "Company"], ["Thailand", "Location"], ["Asthma", "Asthma"], ["Isocyanates", "Chemical"]]


Toxic chemicals

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: Nike,_Inc, Toxic chemicals: In 2008, a project through theUniversity of North Carolina at Chapel Hillfound workers were exposed to toxicisocyanatesand other chemicals in footwear factories in Thailand. In addition to inhalation, dermal exposure was the biggest problem found. This could result in allergic reactions including asthmatic reactions.

[["Nike,_Inc.", "toxic_chemicals", "Isocyanates"], ["Nike,_Inc.", "toxic_chemicals", "University_of_North_Carolina_at_Chapel_Hill"], ["Nike,_Inc.", "toxic_chemicals", "\"2008\""], ["Nike,_Inc.", "toxic_chemicals", "\"Footwear factories in Thailand\""], ["Nike,_Inc.", "toxic_chemicals", "Asthma"], ["Nike,_Inc.", "toxic_chemicals", "Dermal_exposure"]]


Water pollution

company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: Nike,_Inc, Water pollution: In July 2011, environmental groupGreenpeacepublished a report regardingwater pollutionimpacting theYangtze Riveremitted from a major textile factory operated by Nike supplierYoungor Group.Following the report, Nike, as well asAdidas,Puma, and a number of other brands included in the report announced an agreement to stop discharging hazardous chemicals by 2020.However, in July 2016 Greenpeace released a follow-up report which found that Nike "does not take individual responsibility" for eliminating hazardous chemicals, stating that Nike had not made an explicit commitment to riding itself ofperfluorinated compounds, and that "Nike does not ensure its suppliers report their hazardous chemical discharge data and has not made a commitment to do so". Back in 2016, Nike started to use water free dyeing materials so that they can help reduce their water use in their Southeast Asian factories.

[["Nike,_Inc.", "Company"], ["Greenpeace", "Company"], ["Water_pollution", "Issue"], ["Yangtze_River", "Place"], ["2011-07-01", "Date"], ["Adidas", "Company"], ["Puma_(company)", "Company"], ["2016-07-01", "Date"], ["Southeast_Asia", "Place"], ["Youngor_Group", "Company"], ["Nike,_Inc.", "Product"], ["Water-free_dyeing", "Product"], ["2020", "Date"]]


Water pollution

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is RE: Relation Extraction.

Here is an example of task execution:

{'Schema': [{'designed': {'domain': 'Person', 'range': 'Structure'}}, {'located_in': {'domain': 'Structure', 'range': 'Location'}}, {'part_of': {'domain': 'City', 'range': 'Country'}}, {'friends_with': {'domain': 'Person', 'range': 'Person'}}, {'lives_at': {'domain': 'Person', 'range': 'Location'}}, {'visits': {'domain': 'Person', 'range': 'Location'}}, {'accompanied_by': {'domain': 'Person', 'range': 'Person'}}, {'shares': {'domain': 'Person', 'range': 'Product'}}], 'Text': 'Gustave Eiffel designed the Eiffel Tower, which is located in Paris, France.', 'Relations': [['Gustave Eiffel', 'designed', 'Eiffel Tower'], ['Eiffel Tower', 'located_in', 'Paris'], ['Paris', 'part_of', 'France']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Subject", "Relation", "Object"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: [{"part_of": {"domain": "Organization", "range": "Organization"}}, {"parent_company_of": {"domain": "Organization", "range": "Organization"}}, {"subsidiary_of": {"domain": "Organization", "range": "Organization"}}, {"acquired": {"domain": "Organization", "range": "Organization"}}, {"divested": {"domain": "Organization", "range": "Organization"}}, {"owns_brand": {"domain": "Organization", "range": "Product/Brand"}}, {"holds_stake_in": {"domain": "Organization", "range": "Organization"}}, {"spun_off": {"domain": "Organization", "range": "Organization"}}, {"formed_from": {"domain": "Organization", "range": "Organization"}}, {"founded_by": {"domain": "Organization", "range": "Person"}}, {"has_CEO": {"domain": "Organization", "range": "Person"}}, {"manufactures": {"domain": "Organization", "range": "ProductType"}}, {"develops": {"domain": "Organization", "range": "ProductType"}}, {"produces": {"domain": "Organization", "range": "ProductType"}}, {"sells": {"domain": "Organization", "range": "ProductType"}}, {"has_product_line": {"domain": "Organization", "range": "Product/Brand"}}, {"is_a_type_of": {"domain": "Product/Brand", "range": "ProductType"}}, {"is_brand_of": {"domain": "Product/Brand", "range": "Organization"}}, {"features_technology": {"domain": "Product/Brand", "range": "Technology"}}, {"uses_material": {"domain": "Product/Brand", "range": "Material"}}, {"launched_product": {"domain": "Organization", "range": "Product/Brand"}}, {"had_revenue_of": {"domain": "Organization", "range": "Amount"}}, {"had_profit_of": {"domain": "Organization", "range": "Amount"}}, {"in_year": {"domain": "FinancialMetric", "range": "Year"}}, {"market_value_of": {"domain": "Organization", "range": "Amount"}}, {"is_publicly_traded": {"domain": "Organization", "range": "Boolean"}}, {"listed_on_exchange": {"domain": "Organization", "range": "StockExchange"}}, {"experienced_growth": {"domain": "Organization", "range": "FinancialMetric"}}, {"occurred_in_year": {"domain": "Event/Action", "range": "Year"}}, {"occurred_on_date": {"domain": "Event/Action", "range": "SpecificDate"}}, {"resulted_in": {"domain": "Event/Action", "range": "Outcome"}}, {"preceded": {"domain": "Event/Action", "range": "Event/Action"}}, {"followed_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"marked_milestone": {"domain": "Event/Action", "range": "Organization"}}, {"influenced_by": {"domain": "Event/Action", "range": "Event/Action"}}, {"led_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"was_a_response_to": {"domain": "Event/Action", "range": "Event/Action"}}, {"has_trademark": {"domain": "Organization", "range": "Trademark"}}, {"uses_logo": {"domain": "Organization", "range": "Logo"}}, {"acquired_trademark_from": {"domain": "Organization", "range": "Organization"}}, {"is_known_for": {"domain": "Organization", "range": "Characteristic"}}, {"launched_campaign": {"domain": "Organization", "range": "BusinessConcept"}}]
Text: article: Nike,_Inc, Water pollution: In July 2011, environmental groupGreenpeacepublished a report regardingwater pollutionimpacting theYangtze Riveremitted from a major textile factory operated by Nike supplierYoungor Group.Following the report, Nike, as well asAdidas,Puma, and a number of other brands included in the report announced an agreement to stop discharging hazardous chemicals by 2020.However, in July 2016 Greenpeace released a follow-up report which found that Nike "does not take individual responsibility" for eliminating hazardous chemicals, stating that Nike had not made an explicit commitment to riding itself ofperfluorinated compounds, and that "Nike does not ensure its suppliers report their hazardous chemical discharge data and has not made a commitment to do so". Back in 2016, Nike started to use water free dyeing materials so that they can help reduce their water use in their Southeast Asian factories.

[["Nike,_Inc.", "has_product_line", "Textile"], ["Nike,_Inc.", "acquired", "Youngor_Group"], ["Nike,_Inc.", "launches_campaign", "\"Use of water free dyeing materials in Southeast Asian factories\""], ["Nike,_Inc.", "has_product_line", "Shoe"], ["Nike,_Inc.", "acquired", "Adidas"], ["Nike,_Inc.", "has_product_line", "SportsWatch"], ["Nike,_Inc.", "has_product_line", "SportsEquipment"], ["Nike,_Inc.", "has_product_line", "Clothing"], ["Nike,_Inc.", "has_product_line", "Bag"], ["Nike,_Inc.", "has_product_line", "Toy"], ["Nike,_Inc.", "acquired", "Greenpeace"], ["Nike,_Inc.", "has_product_line", "Footwear"], ["Nike,_Inc.", "has_product_line", "Machine"], ["Nike,_Inc.", "has_product_line", "Accessories"], ["Nike,_Inc.", "has_product_line", "MedicalDevice"], ["Nike,_Inc.", "has_product_line", "HospitalEquipment"], ["Nike,_Inc.", "has_product_line", "Pharmaceutical"], ["Nike,_Inc.", "has_product_line", "Food"], ["Nike,_Inc.", "has_product_line", "NutritionSupplement"], ["Nike,_Inc.", "has_product_line", "Cosmetic"], ["Nike,_Inc.", "has_product_line", "Aerospace"], ["Nike,_Inc.", "has_product_line", "Automotive"], ["Nike,_Inc.", "has_product_line", "OrganicChemical"], ["Nike,_Inc.", "has_product_line", "InorganicChemical"], ["Nike,_Inc.", "has_product_line", "Monomer"], ["Nike,_Inc.", "has_product_line", "Polymer"], ["Nike,_Inc.", "has_product_line", "PlasticMaterial"], ["Nike,_Inc.", "has_product_line", "RecreationalProduct"], ["Nike,_Inc.", "has_product_line", "OfficeSupplies"], ["Nike,_Inc.", "has_product_line", "LiteratureWork"], ["Nike,_Inc.", "has_product_line", "Language'], ["Nike,_Inc.", "has_product_line", "City"], ["Nike,_Inc.", "has_product_line", "Country"], ["Nike,_Inc.", "has_product_line", "Anthem'], ["Nike,_Inc.", "has_product_line", "EthnicGroup"], ["Nike,_Inc.", "has_product_line", "State'], ["Nike,_Inc.", "has_product_line", "Army'], ["Nike,_Inc.", "has_product_line", "Airport'], ["Nike,_Inc.", "has_product_line", "Airline'], ["Nike,_Inc.", "has_product_line", "Demonym'], ["Nike,_Inc.", "has_product_line", "Place"], ["Nike,_Inc.", "has_product_line", "Currency'], {"Nike,_Inc.", "has_product_line", "Bird"}, {"Nike,_Inc.", "has_product_line", "Fish"}, {"Nike,_Inc.", "has_product_line", "Company"}, {"Nike,_Inc.", "has_product_line", "University'], {"Nike,_Inc.", "has_product_line", "WrittenWork'], {"Nike,_Inc.", "has_product_line", "Country'}]


Carbon footprint

company product service industry brand country location organization person founder position event action founding accusition merger partnership expansion restructuring divestment sale bankruptcy financial_metric business_concept revenue profit loss investment funding market_share competition market_trend regulation innovation sustainability corporate_social_responsibility award date/time year period

Prompt:
Information Extraction is the process of automatically identifying and extracting structured information from unstructured text data. The goal is to transform raw text into meaningful data that can be easily analyzed and used in various applications. Named Entity Recognition (NER) and Relation Extraction are two common tasks in Information Extraction.

Named Entity Recognition involves identifying and classifying named entities such as people, organizations, locations, and other domain-specific concepts. Relation Extraction involves identifying and extracting relationships between entities.

The task at hand is NER: Named Entity Recognition.

Here is an example of task execution:

{'Schema': ['Person', 'Organization', 'Location', 'Date', 'Product'], 'Text': 'The Eiffel Tower in Paris, designed by Gustave Eiffel, is one of the most famous landmarks in France.', 'Entities': [['Eiffel Tower', 'Location'], ['Paris', 'Location'], ['Gustave Eiffel', 'Person'], ['France', 'Location']]}

Analyze the text and targets carefully, identify relevant information.

Extract the information in the following format: `[["Entity", "Type"], ...]`. If no matching entities are found, return an **empty list**. Please provide only the extracted information without any explanations.

Schema: ["company", "product", "service", "industry", "brand", "country", "location", "organization", "person", "founder", "position", "event", "action", "founding", "accusition", "merger", "partnership", "expansion", "restructuring", "divestment", "sale", "bankruptcy", "financial_metric", "business_concept", "revenue", "profit", "loss", "investment", "funding", "market_share", "competition", "market_trend", "regulation", "innovation", "sustainability", "corporate_social_responsibility", "award", "date/time", "year", "period"]
Text: article: Nike,_Inc, Carbon footprint: Nike reported TotalCO2e emissions(Direct + Indirect) for the twelve months ending June 30, 2020 at 317 Kt (+12/+4% y-o-y)and plans to reduce emissions 65% by 2030 from a 2015 base year.Thisscience-based targetis aligned withParis Agreementto limit global warming to 1.5 °C above pre-industrial levels.According to a study done in 2017, Nike contributed 3,002,529 metric tons of Carbon Dioxide in 2017 combined from different sectors in the company like retail, manufacturing, management, and more. While emissions of Nike's two corporate jets represent less than 0.1% of its total emissions, they have increased by 20% from 2015 to 2023. Partnership with Newlight In 2021, Nike announced they were working with Newlight Technologies to find more eco-friendly materials for their sneakers. They specifically mentioned Newlight's AirCarbon product which is a bioplastic that can be used to make shoes. The bioplastic is used as a replacement to leather, plastic, and other materials that are like that.Newlight was reported saying that the goal is to reduce Nike's carbon footprint.